2.1

7

  1. China

  2. 50 million

  3. 350 million

  4. The graph does not provide the relative frequency, which provides a more accurate answer

9

  1. 69%

  2. 55,200,000 Americans believe divorce is wrong.

  3. Inferential because Gallup is making a claim based on the data presented in the graph.

11

a.18-to-34 year olds: .45 35-to-44 year olds .61

  1. 55+

  2. 18-34

  3. The older the respondants are, the more likely they are to buy products when made in America.

13

Never: .026

Rarely: .068

Sometimes: .116

Most of the time: .263

Always: .527

  1. 57.2%

  2. 9.4%

d e f

my_data <- c(125, 324, 552, 1257, 2518)

groups <- c("Never", "Rarely", "Sometimes", "Most", "Always")

barplot(my_data, main = "Wearing Seatbelts", names.arg = groups)

barplot(my_data, main = "Wearing Seatbelts", names.arg = groups, col = c("red","blue","green","yellow", "black"))

rel_freq <- my_data / sum(my_data)

barplot(rel_freq, main = "Wearing Seatbelts", names.arg = groups, col = c("red","blue","green","yellow","black"))

pie(my_data, labels = groups, main = "Wearing Seatbelts")

  1. Inferential because it is taking the result of a smaller sample and applying it to all college students.

15

More then 1 hour: .3678

Up to 1 hour: .1873

A few time a week: .1288

A few times a month: .0790

Never: .2371

  1. .2371=23.7=24%

c d e

my_data <- c(377, 192, 132, 81, 243)

groups <- c("More 1", "Up to 1", "Few times week", "Few times month", "Never")

barplot(my_data, main = "Use the internet", names.arg = groups)

barplot(my_data, main = "Use the internet", names.arg = groups, col = c("red","blue","green","yellow", "black"))

rel_freq <- my_data / sum(my_data)

barplot(rel_freq, main = "Use the internet", names.arg = groups, col = c("red","blue","green","yellow","black"))

pie(my_data, labels = groups, main = "Use the internet")

  1. There is no data/assurance to support the estimated percentage

2.2

9

  1. 8

  2. 2

  3. 15

  4. 4

  5. 15%

  6. Bell-shaped

10

  1. 4

  2. 9

  3. 16.36%

  4. Right skew

11

  1. 200

  2. 10

  3. 60-69, 2; 70-79, 3; 80-89, 13; 90-99, 42; 100-109, 58; 110-119, 40; 120-129, 31; 130-139, 8; 140-149, 2; 150-159, 1

  4. 100-109

  5. 150-159

  6. 5.5%

  7. No

12

  1. 8

  2. Skip this problem

  3. 0-199

  4. Right skew

  5. The statement is ignoring alcohol as a factor, and is making a false claim because the safeness of roads in this scenario was not the focus of the research. A fair comparison would be: There were more alcohol-related deaths in Texas than in Vermont, because the population is much larger, so the number of alcohol-related deaths could be relative to the population size of both states.

13

  1. Skewed right since the majority of household incomes would fall on the average-low-average side (the left), while the wealthier incomes would be to the far right

  2. Bell-shape because most students who take the SAT fall in the average range, which would be the middle, while the number of those who score high (far right) and the number who score low (far left) is much less.

  3. Skewed right because households that have multiple members (far right) is much less than households that have approximately 4-6 people (far left)

  4. Skewed left because most people who have alzheimers are much older (far right)

14

  1. Bell-shaped because the entire population is taken into account, so the average would fall in the middle while those underaged would be more towards the left (few-none) and the number of heavy drinkers is less than the average

  2. Skewed right because parents may take their kids out of public school as they get older

  3. Skewed left because most patients who were hearing aids are older

  4. Bell-shaped because most men fall in within the average height, while very few are very tall or very short